Method for blindly embedding and extracting a watermark by using wavelet transform and an HVS model

ABSTRACT

The present invention relates to a method for blindly embedding and extracting a watermark by using wavelet transform and a human visual system (HVS) model, which obtains both robustness and invisibility by applying the HVS model of NVF or JND imitating a human visual system to a middle frequency band for wavelet transformation and using a quantization step determined adaptively according to the importance of wavelet coefficient. A method according to the present invention includes the steps of: decomposing an original image by a wavelet and selecting a middle frequency band as a watermark embedment area; obtaining an HVS model having a human visual recognition information at each embedding position; determining the importance of the coefficient for each embedding position, and adaptively determining a quantization step for each embedment location by using the importance and the HVS model; quantizing each pair of embedment area by the quantization step and variably embedding a watermark sequence into a middle frequency band according to a value of the watermark; and performing inverse wavelet transform on an overall area into which the watermark sequence is embedded, and generating a watermarked image.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to watermark embedment and extraction, andmore particularly, to a method for blindly embedding and extracting awatermark by using wavelet transform and a human visual system (HVS)model, which obtains both robustness and invisibility. In the method,the HVS model imitating a human visual system is applied to a middlefrequency band for wavelet transformation and a quantization stepdetermined adaptively according to the importance of wavelet coefficientis used.

2. Description of the Related Art

As a user is charged for using digital contents, it has been activelystudied to protect the copyright of the digital contents. The digitalwatermarking technique is the most widely used copyright protectiontechnique in which information on a copyright holder is embedded intothe digital contents but is not recognized by a human eye. Accordingly,the copyright holder can prove to hold a copyright or an ownership ofthe digital contents by extracting the copyright information from thedigital contents when the digital contents are used or the copyrightdispute occurs.

To achieve the purpose described above, the digital watermarkingtechnique should have properties such as invisibility, robustness andtolerant error detection rate. The invisibility means that the embeddedwatermark cannot be easily recognized by a human eye. The robustnessmeans that the embedded watermark is not destroyed or changed in spiteof intended external conversion, lossy compression, various imageprocesses and noises. However, since the invisibility and the robustnesshave tradeoff relation to each other, one of the most important aims ofthe watermarking technique is to obtain the robustness as well as theinvisibility with minimizing degradation of image quality. Therefore, ithas been actively studied to obtain both the robustness and theinvisibility.

On the other hand, there are two kinds of watermarking techniques: ablind watermarking technique and a non-blind watermarking technique. Inthe blind watermarking technique, the watermark is extracted from thedigital contents without any original data. In the non-blindwatermarking technique, the watermark is extracted from the digitalcontents by using the original data.

The blind watermarking technique does not need any additional storagefor the original data. Recently, the blind watermarking technique isactively studied because of its availability for CertificationAuthority. However, since the blind watermarking technique does not haveany reference data for watermark extraction, it is available but is notrobust against an attack.

Accordingly, the blind watermarking technique has been studiedconsidering a data compression attack and an image processing attacksuch as filtration, especially a geometrical attack that is counted as avery strong attack to the blind watermarking technique.

Most of the techniques against the geometric attack are the watermarkingtechnique for embedding a watermark into the digital contents in afrequency domain by using transforms such as DCT, DFT and DWT.

SUMMARY OF THE INVENTION

Accordingly, the present invention is directed to a method for blindlyembedding and extracting a watermark by using wavelet transform andhuman visual system (HVS) model, which substantially obviates one ormore problems due to limitations and disadvantages of the related art.

It is an object of the present invention to provide a method for blindlyembedding and extracting a watermark by using wavelet transform and anHVS model, which maintains high quality of an image and is very robustagainst the various image processing attacks such as filtration and thedata compression attack. In the method of the present invention, awatermark is combined with the HVS model imitating a human visual systemand embedded into a wavelet middle frequency, and a quantization stepdetermined adaptively according to the importance of wavelet coefficientis used.

Additional advantages, objects, and features of the invention will beset forth in part in the description which follows and in part willbecome apparent to those having ordinary skill in the art uponexamination of the following or may be learned from practice of theinvention. The objectives and other advantages of the invention may berealized and attained by the structure particularly pointed out in thewritten description and claims hereof as well as the appended drawings.

To achieve these objects and other advantages and in accordance with thepurpose of the invention, as embodied and broadly described herein,there is provided a method for blindly embedding a watermark intodigital contents by using a human visual system (HVS) model and wavelettransform. The method includes the steps of: (a) decomposing an originalimage by a wavelet and selecting a middle frequency band as a watermarkembedment area; (b) obtaining an HVS model having a human visualrecognition information at each embedment location; (c) adaptivelydetermining the importance of coefficient value on each embedmentlocation, combining the importance and the HVS model, and adaptivelydetermining a quantization step for each embedding location; (d)quantizing each coefficients pair of embedment area by the quantizationstep and variably embedding a watermark sequence into a middle frequencyband according to a value of the watermark; and (e) performing inversewavelet transform on an overall area into which the watermark sequenceis embedded, to generate a watermarked image.

In another aspect of the present invention, there is provided a methodfor blindly extracting a watermark from digital contents by usingwavelet transform and a HVS model. The method includes the steps of: (a)performing wavelet transform on a watermarked input image with the sameorder of embedment, and calculating a significant coefficient from amiddle frequency band; (b) obtaining the HVS model on each extractionlocation, which was used when embedding the watermark; (c) comparing thesignificant coefficient with absolute value of each coefficient pair ateach extraction location, confirming a quantization step of embedmentfor each extraction location by using the HVS model, and performinginverse quantization on a coefficient pair of each extraction location,thereby extracting the watermark sequence; and (d) calculatingsimilarity between the watermark sequence according to the key valuefrom the user and the extracted watermark sequence, thereby determiningwhether the watermark exists in the digital contents.

It is to be understood that both the foregoing general description andthe following detailed description of the present invention areexemplary and explanatory and are intended to provide furtherexplanation of the invention as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are included to provide a furtherunderstanding of the invention, are incorporated in and constitute apart of this application, illustrate embodiments of the invention andtogether with the description serve to explain the principle of theinvention. In the drawings:

FIG. 1 illustrates a concept of watermark embedment according to thepresent invention;

FIG. 2 illustrates a concept of quantization in watermark embedmentaccording to the present invention;

FIG. 3 illustrates a human visual system (HVS) model using justnoticeable distortion (JND) according to the present invention; and

FIG. 4 illustrates a concept of watermark extraction according to thepresent invention.

DETAILED DESCRIPTION OF THE INVENTION

Reference will now be made in detail to the preferred embodiments of thepresent invention, examples of which are illustrated in the accompanyingdrawings.

In the present invention, considering that human visual system issensitive to variation of low frequency components and high frequencycomponents are vulnerable to image compression process, a watermarksequence is embedded into a middle frequency band to achieve bothrobustness and invisibility.

A pair of coefficients within the middle frequency band have similardistortion characteristics to each other for various image processingattacks and a compression attack. Accordingly, in the present invention,a watermarking technique that has more stable performance by using aquantization step determined differently according to coefficient valuesof the middle frequency band is suggested instead of a method forquantizing a wavelet coefficient by a predetermined size. An HVS modelthat is imitates a human visual system is used so that invisibilityafter watermark embedment is improved.

FIG. 1 illustrates a concept of watermark embedment according to thepresent invention.

Referring to FIG. 1, an original image is decomposed by wavelet with apredetermined step and a watermark is embedded into the middle frequencyband. In the embodiment shown in FIG. 1, the original image isdecomposed by wavelet even in a two-level wavelet decomposition and awatermark sequence is embedded into the middle frequency bands LH2 andHL2. Here, the watermark sequence is a random sequence of 0 and 1determined randomly according to the key value from a user.

In embedding a watermark sequence into a middle frequency band, if thesize of LH2 or HL2 is m×n and the length of the watermark sequence is 1,it is preferable that the watermark sequence is repeatedly embedded by

$\frac{m \times n}{l}$times to improve robustness. For example, a watermark sequence is onceembedded rowwise into a middle frequency band matrix, and then awatermark sequence is sequentially embedded again or a watermarksequence is repeatedly embedded with a predetermined interval.

Meanwhile, one of the main characteristics of the present invention isas follows. A quantization step is adaptively updated according toimportance of wavelet coefficient value and each coefficient valuewithin the middle frequency band is quantized according to the watermarkvalue by using the quantization step so that watermark sequence isembedded.

In more detail, a quarter of the coefficient whose absolute value islargest among all the wavelet coefficients of the middle frequency bandsLH2 and HL2 is selected as a significant coefficient T. The middlefrequency pair (MFP) which corresponds to the same location of themiddle frequency band is made.

If an absolute value of any one coefficient of a coefficient pair islarger than the significant coefficient, a quarter of the absolute valueof the larger coefficient is determined to be a quantization step of thelocation. For example, as shown in FIG. 2, the quantization step isdetermined to be a quarter of the larger coefficient and the smallercoefficient is quantized by using the quantization.

If absolute values of both coefficients of a coefficient pair aresmaller than the significant coefficient, both coefficients arequantized using a predetermined quantization step S. Such predeterminedquantization step S is preferably determined to be an integer that isless than a quarter of the significant coefficient. Experimentally,since the significant coefficient is usually in the range from 15 to 25,the quantization step S is determined to be a proper value in the rangefrom 2 to 5.

Meanwhile, in the present invention, the HVS model that imitates humanpsycho-visual characteristic is used so as to ensure invisibility aftera watermark is embedded. Especially, a perceptual model based on noisevisibility function (NVF) suggested by Voloshynovskiy is used.

The NVF expresses a noise visible degree when a noise is mixed with animage. The NVF gives a different value according to a local region ofimage. The value is in the range from 0 to 1. In other words, the NVFgives 1 in the flat region in which an image does not vary. The NVFgives a value approaching to 0 in the outline or edge region in which animage varies abruptly or rapidly.

The NVF can be obtained from a lowest frequency band LL2 according toequation 1.

$\begin{matrix}{{{nvf}\left( {i,j} \right)} = \frac{\sigma_{x_{\max}}^{2}}{\sigma_{x_{\max}}^{2} + {\theta\;{\sigma_{x}^{2}\left( {i,j} \right)}}}} & {{Equation}\mspace{14mu} 1}\end{matrix}$

where σ_(x) ²(i,j) is a local variance, σ_(x) _(max) ² is a maximumlocal variance, and θ is an adjusting value.

The location (i, j) of the lowest frequency band LL2 corresponds to thesame location (i, j) of the middle frequency bands LH2 and HL2.

Recognition visual mask for each location is calculated substituting NVFinto equation 2.

Equation 2λ=S ₀(1−nvf)+S ₁ ·nvf

where S₀ is watermark embedment strength of a edge region of the imageand S₁ is watermark embedment strength of a flat region of the image.

The strength S₁ of the NVF of the flat region is set to be weak and thestrength S₀ of (1−NVF) of the edge region is set to be strong so thatthe recognition visual mask is obtained. For example, S₀, S₁ and θ areset as follows: S₀=20, S₁=5 and θ=150.

When the recognition visual mask is obtained as described above, thelocation into which the watermark is strongly embedded is confirmedusing equation 3, and the quantization step for watermark embedment isobtained according to equation 4.

$\begin{matrix}{{{NVFAcpt}\left( {i,j} \right)} = \left\{ \begin{matrix}1 & {{{if}\mspace{14mu}{\lambda\left( {i,j} \right)}} > {threshold}} \\0 & {otherwise}\end{matrix} \right.} & {{Equation}\mspace{14mu} 3} \\{{{Quantize\_ step}\left( {i,j} \right)} = \left\{ \begin{matrix}{{maxcoef}/4} & {{{if}\mspace{14mu}{{NVFAcpt}\left( {i,j} \right)}} == {1\mspace{14mu}{and}}} \\\; & {{{one}\mspace{14mu}{of}\mspace{14mu}{{MFP}\left( {i,j} \right)}} > {{significant}\mspace{14mu}{coefficient}}} \\S & {otherwise}\end{matrix} \right.} & {{Equation}\mspace{14mu} 4}\end{matrix}$

where MFP(i,j) is a coefficient pair of the middle frequency band and Sis a quantization step defined as small value (e.g. 3) in advance.

Description will be made on equation 4. If the value of NVFAcpt(i,j)confirmed by the recognition visual mask as represented in equation 3 is1 and an absolute value of any one coefficient of a coefficient pair ofthe middle frequency bands LH2 and HL2 is larger than the significantcoefficient T, a quarter of the absolute value of the larger coefficientis determined to be a quantization step and the smaller coefficient isquantized by the quantization step so that a watermark is embedded.

In other case, if the value of NVFAcpt(i,j) is 0 or absolute values ofboth coefficients of a coefficient pair are smaller than the significantcoefficient T, the coefficients of the middle frequency bands LH2 andHL2 are both quantized using a preset quantization step S.

On the other hand, in another embodiment to ensure invisibility, an HVSmodel is obtained using a just noticeable distortion (JND) instead ofthe NVF.

FIG. 3 illustrates a process in which a JND value is obtained in theoriginal image and JND acceptability for each location is determined.

Referring to FIG. 3, JND value for each pixel of the original image isobtained using pixel-wise JND estimation.

The original image is divided into blocks of a size of 4 pixels×4pixels. If all the JND values of 16 pixels are larger than apredetermined threshold (e.g. average of JND values of an overall image)in each block, it is regarded that the block has JNDAcpt(i,j)=1, thatis, JND-acceptable and the coefficients of the middle frequency bandsLH2 and HL2 corresponding to the block are JND-acceptable.

It can be represented as equation 5. When using JND method, the value ofJNDAcpt(i,j) instead of the value of NVFAcpt(i,j) is substituted intoequations 4, 6 and 7.

$\begin{matrix}{{{JNDAcpt}\left( {i,j} \right)} = \left\{ \begin{matrix}1 & \begin{matrix}{{{if}\mspace{14mu}{JND}\mspace{14mu}{value}\mspace{14mu}{of}\mspace{14mu}{each}}{\mspace{25mu}\;}} \\{{{pixel}\mspace{14mu}{in}\mspace{14mu}{block}\mspace{11mu}\left( {i,j} \right)\mspace{14mu}{is}}\;} \\{{larger}\mspace{14mu}{than}\mspace{14mu}{threshold}}\end{matrix} \\0 & {otherwise}\end{matrix} \right.} & {{Equation}\mspace{14mu} 5}\end{matrix}$

When quantization step is determined for each embedment location asdescribed above, the coefficient of the middle frequency band LH2 or HL2is quantized according to watermark value to be embedded as equation 6so that a watermark sequence is embedded.

Equation 6

For all the LH2 and HL2 coefficients

If (abs(LH2(i,j))<T && abs(HL2(i,j))||NVFAcpt(i,j)==0)

-   A. Quantize LH2(i,j) and HL2(i,j) by S;

Else

-   A. Maxcoef=max(abs(LH2(i,j)), abs(HL2(i,j)));-   B. Step=Maxcoef/D;-   C. If Maxcoef==abs(LH2(i,j))-   D. Quantize abs(HL2(i,j)) by Step;-   E. Else-   F. Quantize abs(LH2(i,j)) by Step;-   G. End if

Else if

Else for

Equation 6 means as follows.

If the absolute values of both coefficients LH2(i,j) and HL2(i,j) of themiddle frequency bands are smaller than the significant coefficient T orNVFAcpt(i,j) is 0, both coefficients are divided by the quantizationstep S of the predetermined smaller value. Otherwise, the smallercoefficient of the two coefficients is divided by a quarter of thelarger coefficient.

If the value of the watermark to be embedded is 1, the division resultis rounded off to the nearest odd number. If the value of the watermarkto be embedded is 0, the division result is rounded off to the nearesteven number. The rounded-off division result is quantized and multipliedby each quantization step so that a target coefficient value is changedaccording to the watermark value.

Referring to FIG. 2, for example, if coefficients L and S of somecoefficient pair are 32 and 18 respectively and their NVFAcept value andthe significant coefficient are 1 and 20 respectively, the quantizationstep is 8 (=32 (coefficient L)/4) according to equation 4. If thesmaller coefficient is divided by the quantization step S, the divisionresult is 2.25 (=18 (coefficient S)/8). Here, if the watermark value is1, the smaller coefficient is rounded off and quantized to be odd number3. Then, the odd number 3 is multiplied by the quantization step 8 sothat the smaller coefficient is changed to 24 (=3×8). On the other hand,if the watermark value to be embedded is 0, the smaller coefficient isquantized to be even number 2 and the even number 2 is multiplied by thequantization step 8 so that the smaller coefficient is changed to 16(=2×8).

As described above, if a watermark sequence is repeatedly embedded intothe middle frequency bands LH2 and HL2, inverse wavelet transform isperformed on the overall frequency band to generate a watermarked image.

On the other hand, FIG. 4 illustrates schematically a watermarkextraction process according to the present invention.

Referring to FIG. 4, in the watermark extraction process of the presentinvention, two-step wavelet transform identical to that of embedment isperformed on the watermarked image, and then the significant coefficientT is obtained in the middle frequency band as described above.

As described on the equations 1 to 4, NVFAcpt(i,j) is obtained from LL2and absolute values of a coefficient pair are compared with thesignificant coefficient T so that the watermark sequence W* is extractedas equation 7. Of course, when using JND instead of NVF, JNDAcpt(i, j)is obtained from the watermarked overall image as described above. Inequation 7, JNDAcpt(i, j) is substituted for NVFAcpt(i, j) in equation7.

Equation 7

For all the LH2 and HL2 coefficients

If (abs(LH2(i,j))<T && abs(HL2(i,j)<T)||NVFAcpt(i,j)==0)

-   A. W*(i,j)=(LH2(i,j)/S mod 2+HL2(i,j)/S mod 2)/2;

Else

-   A. Maxcoef=max(abs(LH2(i,j)), abs(HL2(i,j)));-   B. Step=Maxcoef/D;-   C. If Maxcoef==abs(LH2(i,j))-   D. W*(i,j)=HL2(i,j)/Step mod 2;-   E. Else-   F. W*(i,j)=LH2(i,j)/Step mod 2;-   G. End if

End if

Else for

Equation 7 will be described. If absolute values of both coefficients ofa coefficient pair are smaller than the significant coefficient orNVFAcpt(i,j)=0, each coefficient is divided by the predetermined smallquantization step S, remainders are obtained by dividing the divisionresult by two, the remainders are averaged and the watermark isextracted. Here, integer sequence of 0 and 1 is extracted as thewatermark by using round-off.

On the other hand, if an absolute value of any one coefficient of acoefficient pair is larger than the significant coefficient andNVFAcpt(i,j)=1, a quarter of the absolute value of the largercoefficient is determined to be a quantization step, the smallercoefficient is divided by the quantization step, a remainder areobtained by dividing the division result by two, and the remainder 0 or1 is extracted as the watermark.

Here, when a watermark sequence is repeatedly embedded, the watermarksequence is extracted as much as the number of repeat and then, bits ofthe same location are averaged, so that more reliable watermark sequencecan be calculated. Here, it is preferable that bits are averaged withtheir quantization step as their weight rather than performing thesimple average.

0 is replaced with −1 to change the extracted watermark sequence intobipolar sequence that has −1 and +1.

According to the process described above, when the watermark sequence W*is extracted from a digital contents, the watermark sequence W* iscompared with a watermark sequence W according a key value from a userand similarity is calculated. If the similarity is larger than apredetermined threshold, it is determined that a watermark, that is, acopyright is embedded into the digital contents.

The method for blindly embedding and extracting a watermark by usingwavelet transform and an HVS model according to the present inventiondescribed above can be stored in record media from which a computer canretrieve information. Such record media include all the types of recordmedia in which programs and data are stored: for example, a read onlymemory (ROM), a random access memory (RAM), a compact disk (CD)-ROM, adigital video disk (DVD)-ROM, a magnetic tape, a floppy disk, an opticaldata storage, etc. Such record media are distributed to computer systemsconnected to network and store codes that can be read and executed by acomputer.

As described above, in the method for blindly embedding and extracting awatermark by using wavelet transform and an HVS model according to thepresent invention, a watermark sequence is combined with an HVS modelimitating a human visual system and embedded into the middle frequencyband of wavelet transformation so that the watermark is robust againstexternal attacks and good image quality is maintained even after awatermark is embedded. Invisibility is improved.

A uniform quantization step is not used but the quantization stepadaptively determined according to the importance of coefficients of themiddle frequency band is used to minimize degradation of image qualityand make the watermark robust against various image process attacks suchas filtration and data compression.

It will be apparent to those skilled in the art that variousmodifications and variations can be made in the present invention. Thus,it is intended that the present invention covers the modifications andvariations of this invention provided they come within the scope of theappended claims and their equivalents.

1. A method for blindly embedding a watermark into digital contents byusing a human visual system (HVS) model and wavelet transform, themethod comprising the steps of: (a) decomposing an original image by awavelet and selecting a middle frequency band as a watermark embedmentarea; (b) obtaining an HVS model having a human visual recognitioninformation at each embedment location; (c) adaptively determining theimportance of coefficient value on each embedment location, combiningthe importance and the HVS model, and adaptively determining aquantization step for each embedding location; (d) quantizing eachcoefficients pair of embedment area by the quantization step andvariably embedding a watermark sequence into a middle frequency bandaccording to a value of the watermark; and (e) performing inversewavelet transform on an overall area into which the watermark sequenceis embedded, to generate a watermarked image; wherein step (c) furthercomprises the steps of: selecting, as a significant coefficient, aquarter of the coefficient whose absolute value is largest among all thecoefficients of the middle frequency band; and comparing the significantcoefficient with coefficient absolute value of each coefficient pairwithin the middle frequency band to determine importance of thecoefficient value at each location.
 2. The method of claim 1, whereinthe step (a) comprises the steps of: performing wavelet transform on theoriginal image by two or more steps; and defining the middle frequencyband of the final step as a watermark embedment area.
 3. The method ofclaim 1, wherein the step (b) comprises the steps of: obtaining a noisevisibility function (NVF) for each location from a lowest frequency bandaccording to a following equation:${{nvf}\left( {i,j} \right)} = \frac{\sigma_{x_{\max}}^{2}}{\sigma_{x_{\max}}^{2} + {\theta\;{\sigma_{x}^{2}\left( {i,j} \right)}}}$where σ_(x) ²(i,j) is a local variance, σ_(x) _(max) ² is a maximumlocal variance, and θ is an adjusting value; calculating a recognitionvisual mask by substituting the NVF into a following equation:λ=S₀(1−nvf)+S₁·nvf where S₀ is watermark embedment strength of an edgeregion of the image and S₁ is watermark embedment strength of a flatregion of the image; and evaluating acceptability of the NVF dependingon whether the calculated recognition visual mask exceeds a threshold,thereby obtaining the HVS model at each location.
 4. The method of claim1, wherein the step (b) comprises the steps of: (b-1) decomposing theoriginal image into blocks as many as the number of pixels of the middlefrequency band; and (b-2) evaluating whether or not to accept justnoticeable distortion (JND) at each block, thereby obtaining the HVSmodel on each embedding location.
 5. The method of claim 4, wherein inthe step (b-2), if all the JND values of all the pixels of each blockare greater than a predetermined threshold, the embedding locationcorresponding to the block is determined to accept JND and the HVS modelon each embedding location is obtained.
 6. The method of claim 1,wherein, in the step (c), if an absolute value of any one coefficient ofa coefficient pair within the middle frequency band is larger than thesignificant coefficient and the embedding location is NVF-acceptable orJND-acceptable by the HVS model, a quarter of the absolute value of thelarger coefficient is set to be a quantization step of the location andthe smaller coefficient is set to be a watermarking target.
 7. Themethod of claim 1, wherein, in the step (c), if absolute values of bothcoefficients of a coefficient pair within the middle frequency band aresmaller than the significant coefficient or the embedding location isnot NVF-acceptable nor JND-acceptable by the HVS model, a presetquantization step is applied to the location and both of thecoefficients are set to be watermarking targets.
 8. The method of claim7 wherein, in the step (c), if the embedding location is notNVF-acceptable nor JND-acceptable by the HVS model or absolute values ofboth coefficients of a coefficient pair within the middle frequency bandare smaller than the significant coefficient, a quarter of thesignificant coefficient is set to be a quantization step of theembedment location.
 9. The method of claim 1, wherein the step (d)comprises the steps of: dividing a target coefficient value by aquantization step of each location; quantizing the division result byrounding the division result off to an approximate odd or even numberaccording to a watermark value; multiplying the quantization step to thequantization result, thereby updating the target coefficient value; andembedding the watermark into the digital contents.
 10. The method ofclaim 1, wherein step (d) further comprises repeatedly embedding intothe middle frequency band a watermark sequence determined randomlyaccording to a key value from a user.
 11. A method for blindlyextracting a watermark from digital contents by using wavelet transformand a HVS model, the method comprising the steps of: (a) performingwavelet transform on a watermarked input image with the same order ofembedment, and calculating a significant coefficient from a middlefrequency band; (b) obtaining the HVS model on each extraction location,which was used when embedding the watermark; (c) comparing thesignificant coefficient with absolute value of each coefficient pair ateach extraction location, confirming a quantization step of embedmentfor each extraction location by using the HVS model, and performinginverse quantization on a coefficient pair of each extraction location,thereby extracting the watermark sequence; and (d) calculatingsimilarity between the watermark sequence according to the a key valuefrom the user and the extracted watermark sequence, thereby determiningwhether the watermark exits in the digital contents; wherein step (c)comprises one of: c1) determining that absolute values of bothcoefficients of a coefficient pair of the extraction location aresmaller than the significant coefficient, or the HVS model is neitherNVF, nor JND acceptable; dividing both coefficients by a predeterminedquantization step; obtaining remainders by dividing the division resultby two; averaging the remainders; and extracting the watermark; c2)determining that an absolute value of any one coefficient of acoefficient pair of the extraction location is larger than thesignificant coefficient and that the HVS model is NVF-acceptable orJND-acceptable; determining a quantization step to be a quarter of theabsolute value of the larger coefficient; dividing the smallercoefficient by the determined quantization step; obtaining a remainderby dividing the division result by two; extracting the watermark usingthe remainder; and c3) determining that an absolute value of any onecoefficient of a coefficient pair within the middle frequency band islarger than the significant coefficient; determining that the embeddinglocation is NVF or JND acceptable by the HVS model; setting aquantization step of the location equal to a quarter of the absolutevalue of the larger coefficient; and setting the smaller coefficient tobe a watermarking target.
 12. The method of claim 11, wherein, in thestep (a), a quarter of the coefficient whose absolute value is largestamong all the coefficients of the middle frequency band is selected as asignificant coefficient.
 13. The method of claim 11, wherein step (b)further comprises obtaining NVF acceptability and JND acceptabilityusing the HVS model of each extraction location.
 14. The method of claim11, wherein, in the step (c), if the watermark sequence is repeatedlyembedded into the digital contents, the watermark sequences areextracted as many as the repeat times, each bit of the same location isweighted with the quantization step and averaged, and a final marksequence is calculated.
 15. The method of claim 4, wherein, in the step(c), if an absolute value of any one coefficient of a coefficient pairwithin the middle frequency band is larger than the significantcoefficient and the embedding location is NVF-acceptable orJND-acceptable by the HVS model, a quarter of the absolute value of thelarger coefficient is set to be a quantization step of the location andthe smaller coefficient is set to be a watermarking target.
 16. Themethod of claim 5, wherein, in the step (c), if an absolute value of anyone coefficient of a coefficient pair within the middle frequency bandis larger than the significant coefficient and the embedding location isNVF-acceptable or JND-acceptable by the HVS model, a quarter of theabsolute value of the larger coefficient is set to be a quantizationstep of the location and the smaller coefficient is set to be awatermarking target.
 17. The method of claim 1, wherein, in the step(c), if an absolute value of any one coefficient of a coefficient pairwithin the middle frequency band is larger than the significantcoefficient and the embedding location is NVF-acceptable orJND-acceptable by the HVS model, a quarter of the absolute value of thelarger coefficient is set to be a quantization step of the location andthe smaller coefficient is set to be a watermarking target.
 18. Themethod of claim 3, wherein, in the step (c), if absolute values of bothcoefficients of a coefficient pair within the middle frequency band aresmaller than the significant coefficient or the embedding location isnot NVF-acceptable nor JND-acceptable by the HVS model, a presetquantization step is applied to the location and both of thecoefficients are set to be watermarking targets.
 19. The method of claim4, wherein, in the step (c), if absolute values of both coefficients ofa coefficient pair within the middle frequency band are smaller than thesignificant coefficient or the embedding location is not NVF-acceptablenor JND-acceptable by the HVS model, a preset quantization step isapplied to the location and both of the coefficients are set to bewatermarking targets.
 20. The method of claim 5, wherein, in the step(c), if absolute values of both coefficients of a coefficient pairwithin the middle frequency band are smaller than the significantcoefficient or the embedding location is not NVF-acceptable norJND-acceptable by the HVS model, a preset quantization step is appliedto the location and both of the coefficients are set to be watermarkingtargets.
 21. The method of claim 1, wherein, in the step (c), ifabsolute values of both coefficients of a coefficient pair within themiddle frequency band are smaller than the significant coefficient orthe embedding location is not NVF-acceptable nor JND-acceptable by theHVS model, a preset quantization step is applied to the location andboth of the coefficients are set to be watermarking targets.
 22. Themethod of claim 13, wherein, in the step (c), if absolute values of bothcoefficients of a coefficient pair of the extraction location aresmaller than the significant coefficient or the HVS model is notNVF-acceptable nor JND-acceptable, two coefficients are divided by apredetermined quantization step, remainders are obtained by dividing thedivision result by two, the remainders are averaged and the watermark isextracted.
 23. The method of claim 13, wherein, in the step (c), if anabsolute value of any one coefficient of a coefficient pair of theextraction location is larger than the significant coefficient and theHVS model is NVF-acceptable or JND-acceptable, a quarter of the absolutevalue of the larger coefficient is determined to be a quantization step,the smaller coefficient is divided by the quantization step, a remainderare obtained by dividing the division result by two, and the watermarkis extracted using the remainder.